Randomized algorithms
Connecting the Physical World with Pervasive Networks
IEEE Pervasive Computing
Tracking a moving object with a binary sensor network
Proceedings of the 1st international conference on Embedded networked sensor systems
Distributed particle filters for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Distributed state representation for tracking problems in sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
A distributed algorithm for managing multi-target identities in wireless ad-hoc sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Tracking multiple targets using binary proximity sensors
Proceedings of the 6th international conference on Information processing in sensor networks
On the Deterministic Tracking of Moving Objects with a Binary Sensor Network
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
An Energy-Efficient Object Tracking Algorithm in Sensor Networks
WASA '08 Proceedings of the Third International Conference on Wireless Algorithms, Systems, and Applications
Location-Free Object Tracking on Graph Structures
EuroSSC '08 Proceedings of the 3rd European Conference on Smart Sensing and Context
Target Counting under Minimal Sensing: Complexity and Approximations
Algorithmic Aspects of Wireless Sensor Networks
Brief paper: Decentralized estimation and control of graph connectivity for mobile sensor networks
Automatica (Journal of IFAC)
Distributive target tracking in sensor networks with a Markov random field model
IROS'09 Proceedings of the 2009 IEEE/RSJ international conference on Intelligent robots and systems
Average consensus based scalable robust filtering for sensor network
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Sensor selection for target tracking in binary sensor networks using particle filter
Sarnoff'10 Proceedings of the 33rd IEEE conference on Sarnoff
A distributed topological camera network representation for tracking applications
IEEE Transactions on Image Processing - Special section on distributed camera networks: sensing, processing, communication, and implementation
Multiple-Target Tracking With Binary Proximity Sensors
ACM Transactions on Sensor Networks (TOSN)
Analysis of Deterministic Tracking of Multiple Objects Using a Binary Sensor Network
ACM Transactions on Sensor Networks (TOSN)
Focused most probable world computations in probabilistic logic programs
Annals of Mathematics and Artificial Intelligence
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This paper considers the problem of tracking objects with sparsely located binary sensors. Tracking with a sensor network is a challenging task due to the inaccuracy of sensors and difficulties in sensor network localization. Based on the simplest sensor model, in which each sensor reports only a binary value indicating whether an object is present near the sensor or not, we present an optimal distributed tracking algorithm which does not require sensor network localization. The tracking problem is formulated as a hidden state estimation problem over the finite state space of sensors. Then a distributed tracking algorithm is derived from the Viterbi algorithm. We also describe provably good pruning strategies for scalability of the algorithm and show the conditions under which the algorithm is robust against false detections. The algorithm is also extended to handle non-disjoint sensing regions and to track multiple moving objects. Since the computation and storage of track information are done in a completely distributed manner, the method is robust against node failures and transmission failures. In addition, the use of binary sensors makes the proposed algorithm suitable for many sensor network applications.